As you can see, a sensitivity of 95% (true positive 95% of the time) with a confidence interval +- 4.3% requires 100 positive subjects. Because the natural rate is 1 in 500, we would need 500*100 = 50,000 total subjects. So you can see how absolutely ludicrous it is to say a woman sniffs the clothes of 12 subjects and is presumed to have a 100% true positive rate with 100% confidence level.
You clearly need to take stats again, because you don't understand what you're citing. A 95% confidence interval is not the same thing as a hypothesis test of p<.05. A confidence interval is for estimating the uncertainty that your chosen margin of error will include the true population parameter.
Nobody's claiming she's always 100% accurate. That's also a factor of low sample sizes. But I went ahead and computed the margin of error for you. For n=12, a 95% confidence interval requires a margin of error of 28%, so her true detection ability is, at worst, 72%, which is still higher than anything else we've got.
As you can see, a sensitivity of 95% (true positive 95% of the time) with a confidence interval +- 4.3% requires 100 positive subjects. Because the natural rate is 1 in 500, we would need 500*100 = 50,000 total subjects. So you can see how absolutely ludicrous it is to say a woman sniffs the clothes of 12 subjects and is presumed to have a 100% true positive rate with 100% confidence level.